BootCP {CPEg}R Documentation

Bootstrap estimate of mis-classification rates

Description

Bootstrapping is used to estimate the mis-classification rate of a classification algorithm.

Usage

BootCP(X, y, Xt, yt, fun = FitLDA, NREP = 10, nTrain = nrow(X))

Arguments

X original training data inputs
y original training data output
Xt original test data inputs
yt original test data output
fun the classification function
NREP number of bootstrap replications
nTrain size of training sample, default is same as inputs

Details

The training and test data are combined.

Value

matrix giving the average mis-classfication rates in the training and test samples and the corresponding standard deviations

Author(s)

AIM

See Also

FitLDA

Examples

data(Mixture)
attach(Mixture)
BootCP(X,y,Xt,yt, NREP=15, fun=function(a,b,c,d) FitkNN(a,b,c,d,k=7) )

[Package CPEg version 1.1 Index]